no code implementations • 18 Apr 2018 • Aya Abdelsalam Ismail, Timothy Wood, Héctor Corrada Bravo
State-of-the-art forecasting methods using Recurrent Neural Net- works (RNN) based on Long-Short Term Memory (LSTM) cells have shown exceptional performance targeting short-horizon forecasts, e. g given a set of predictor features, forecast a target value for the next few time steps in the future.
1 code implementation • NeurIPS 2020 • Aya Abdelsalam Ismail, Mohamed Gunady, Héctor Corrada Bravo, Soheil Feizi
Saliency methods are used extensively to highlight the importance of input features in model predictions.
1 code implementation • NeurIPS 2021 • Aya Abdelsalam Ismail, Héctor Corrada Bravo, Soheil Feizi
In this paper, we tackle this issue and introduce a {\it saliency guided training}procedure for neural networks to reduce noisy gradients used in predictions while retaining the predictive performance of the model.